{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "多项式回归"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "x=np.random.uniform(-3,3,size=100)\n",
    "X=x.reshape(-1,1)\n",
    "y=0.5*x**2+x+2+np.random.normal(size=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(x,y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "lin_reg=LinearRegression()\n",
    "lin_reg.fit(X,y)\n",
    "y_predict=lin_reg.predict(X)\n",
    "plt.scatter(x,y)\n",
    "plt.plot(x,y_predict,color=\"r\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "解决方案：新加一个特征X2（x²）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(100, 2)"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X2=np.hstack([X,X**2])\n",
    "\n",
    "X2.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "lin_reg2=LinearRegression()\n",
    "lin_reg2.fit(X2,y)\n",
    "y_predict2=lin_reg2.predict(X2)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2cf57f5e070>]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(x,y)\n",
    "\"\"\"需要进行排序和sort索引（对x）的y\"\"\"\n",
    "plt.plot(np.sort(x),y_predict2[np.argsort(x)],color=\"r\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1.00327532, 0.48367741])"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lin_reg2.coef_#查看参数：第一个系数是X的系数，第二个是X²的系数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.0726058604882613"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lin_reg2.intercept_#截距"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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